AI in Requirements Engineering (RE) relies on industrial data, yet safety and privacy risks limit its use. While the GDPR distinguishes only between anonymization and pseudonymization, we use neutralization as a semantics-preserving technique. In AI-supported RE, data heterogeneity and cross-domain variability impede model training. We propose guidelines for semantics-preserving preprocessing for RE datasets based on ISO 29148 criteria, showing that neutralization does not compromise semantics. The approach enables industry–academia collaboration through AI-assisted RE in product development.

Academic tools for sustainable product development often fail to achieve widespread use in industry. Based on a case study of a consultancy firm, this study explores factors that enable consultants to adopt and adapt such tools and act as intermediaries that translate and integrate academic findings into practice. Interviews and a survey revealed that a solid conceptual foundation, clear client value, result visualization, adaptability, and integration with existing workflows are most important, and the study proposes nine lessons learned to guide future tool development and collaboration.

This paper provides a structured overview of methods for assessing assembly complexity in manufacturing. A systematic literature review classifies approaches as product-, information-, or system-centered, each reflecting distinct sources of complexity and application contexts. A four-dimensional scheme enables consistent comparison. The results highlight methodological gaps and support future development of scalable, integrable models for planning and decision-making in high-variety production environments.

While Immersive Reality (XR) design tools continue to emerge, the industry perspective on their value is unclear. This paper presents outputs of a workshop with 16 design experts testing a wide range of XR design tools. Value exceeding that of traditional tools was reported, driven by human-centric affordances like flexibility, interactivity, and response rate. Perceived detriments were linked to implementation challenges, such as fidelity and skill. Findings validate XR’s potential in design and direct future work towards overcoming key technical hurdles to unlock its value.

Building and maintaining a digital twin requires considerable technical and financial effort. Thus, its economic viability depends on creating value across the full product lifecycle to balance the initial costs. Therefore, this study examines what potentials and challenges arise from the use of the Digital Twin throughout the product lifecycle with regard to its benefits for product development, using a systematic literature review. The identified factors were clustered and mapped to key components, highlighting the strengths and weaknesses of the individual components of the digital twin.

This study systematically characterizes product development processes (PDPs) in hardware-oriented SMEs. A PRISMA-based literature review identifies twelve empirical case studies and eight development frameworks. The analysis derives key PDP influence factors, synthesizes stage-wise SME PDP activities, and consolidates characteristic challenges. A gap analysis reveals the absence of SME-specific PDP development frameworks and missing integration with technology management. The results establish a structured empirical basis for future research.

The applicability and scalability of design adaptations utilizing reinforcement learning can be broadened by using graph-based approaches instead of rigid vector- or grid-based ones. However, graph-based approaches often require a high number of simulations to converge. To reduce the simulation effort in the mechanical optimisation, the reinforcement learning setup is enriched with task-specific causal and physically based information. This work systematically investigates the influence of this additional information on the efficiency of design adaptations using a factorial test design.

Electronic waste is one of the fastest-growing waste streams, yet only a small fraction is properly recycled. Many challenges in recycling originate in product design; for example the choice of materials and joining methods. This paper presents the first version of the Design for Recycling of Electronics Guide, developed to bridge the gap between design and recycling practice. Based on case studies, shredding experiments, and method reviews, it provides practical guidance to help designers anticipate and improve recyclability during product development.

Implementing novel interaction modalities to CAD systems is raising questions about suitability of types of thinking employed and appropriateness of existing workflows used in CAD in this new context. The study reported in this paper explores the potential for introduction of alternative activities into existing workflows, proposed by designers interacting with 3D shapes using gestural interaction. Findings propose introduction of sculpting and forming paradigms that may reduce the amount of work required to create more complex forms.

We reviewed 36 web-based toolkits supporting health and care design and improvement and identified five classification dimensions: novelty (novel or established tools), scope (specialised or generic), origin (research- or practice-based), motivation for use (risk reduction or benefit enhancement), and application level (individual or group use). We also identified five types of toolkit developers and seven end-user roles. Most toolkits were generic and practice-based, developed by commercial or academic actors, targeted at practitioners and leaders, and supported both individual and group use.

Social robots increasingly interact with humans in diverse contexts. In this study, a systematic framework is proposed for selecting stakeholders based on the user requirements in participatory design of social robots. Matching social robot design dimensions with stakeholder fields in the framework, is achieved using Quality Function Deployment (QFD) and Design Structure Matrix (DSM) methodologies. A case study is presented to demonstrate utilization of the framework. The contribution of this paper is to develop an infrastructure towards formalization of participatory design of social robots.

Implementing circular business models (CBMs) like Product-as-a-Service entails high uncertainty, necessitating costly and prolonged business experimentation. To efficiently mitigate this uncertainty, Bayesian Optimal Experimental Design is applied to the CBM context, selecting conditions that maximize the Expected Information Gain for unknown CBM parameters. Applied to an air conditioner subscription case study, the method successfully identified optimal conditions from 124 candidates. This approach facilitates CBM implementation by efficiently minimizing uncertainty under limited resources.

This paper evaluates the criticality assessment within the Criticality-Based Planning of Prototype Sequences method. Two independent application studies investigate whether the existing scale definitions for novelty, technical difficulty and importance are sufficient for systematic and context-independent use. The results show that operationalised criteria and clearer evaluator guidance significantly improve consistency, reproducibility and applicability across different development projects.

This study examines designers’ cognitive and emotional experiences during the design thinking process and the effect of time constraints. Using the MetaCogno tool, 83 participants reported moment-to-moment experiences across Problem Analysis, Ideation, Evaluation, and Sketching. Positive experiences dominated, with time-limited designers showing higher enjoyment, focus, and engagement. Findings highlight the dynamic interplay of cognition and emotion, and suggest that time pressure can enhance focus and motivation during design.

To design effective behaviour changing interventions, behavioural designers need to generate ideas that combine both technical and behavioural aspects. However, little is still known about the creative output of ideation in behavioural design. Taking an exploratory approach, this study examines the creative characteristics of brainstormed behavioural design ideas using the Behavioural Design Space (BDS) as creative assessment framework. The findings show uneven distributions across all BDS parameters indicating fixation and lost creative opportunities.

This study investigates how product attributes shape user interpretation of unfamiliar products in terms of functions and context of use. This was made possible through an experiment involving 71 participants who were administered three unfamiliar end-use products without any additional cue. Findings reveal that visual cues, material semantics, and contextual imagination shape understanding, with misinterpretations often arising from analogical reasoning and partial cue activation. Designers should harmonize cues and leverage material symbolism to guide user perception and acceptance.

Bridging the intention-action gap is key to driving sustainable consumer behavior. In this paper, we introduce the Change Factory, a methodology that applies behavioral science to design sustainable product experiences. We detail its four-step CODE framework – Change, Obstacles, Design, and Experimentation – and illustrate its application on fragrance refill. After identifying behavioral barriers, 33 gentle intervention ideas were generated to promote refill adoption, validating the method’s efficacy in translating behavioral insights into concrete, behavior-driven design solutions.

This study introduces an NLP-based Memory Model that structures how framing and reframing evolve throughout design. Grounded in constructive and situated memory theories, it models memory as a dynamic system of activation and decay, enabling measurement of the number and semantic value of frames in design discourse. Analyses of architecture students’ sessions show framing peaks during exploration and declines as solutions stabilize. They also show semantic diversity cycles through expansion and narrowing, revealing framing as a continuous, memory-driven reinterpretive process.

This paper explored the Double Diamond design methodology through a low-reliance pacifier case study that reframes parents’ needs into a child-led weaning solution. The project integrates artistic design research with engineering design innovation methodology to create an unique aesthetic floral pacifier idea with functional forms. It was found that beyond academic theory, effective real-world design requires dedicated testing and refinement, positioning this work as a practice-led research approach that strengthens both process and outcome for a successful and modular design process.

This study investigates the gap between objective and subjective garment quality and explores how insights from subjective quality can inform industry practices to enhance product longevity. Based on 16 interviews, findings reveal that consumers rely on subjective-intuitive aspects to form quality expectations and subjective-aligned aspects that emerge through experiences. Qualitative use emerges as a crucial connection between subjective and objective quality. These insights inform design strategies promoting garment longevity across three phases: design, primary retail, and secondary retail.